Apache Kafka for Programmers Training Course

Introduction

• Overview of Apache Kafka
• Basics of event streaming and real-time data processing
• Key features and capabilities of Apache Kafka
• Applications and advantages of Kafka in modern software development

Kafka Architecture and Core Principles

• Architectural components: brokers, topics, partitions, and replicas
• The roles of producers and consumers in message publishing and consumption
• The function of ZooKeeper within the Kafka ecosystem

Kafka Topics and Partitioning

• Creating and configuring topics
• Partition logic and its impact on system behavior
• Replication strategies and fault tolerance mechanisms

Building Kafka Producers

• Implementing producers across various programming languages
• Message serialization methods and techniques
• Optimal producer configurations and industry best practices

Building Kafka Consumers

• Developing consumers in different programming environments
• Setting up consumer groups and managing offsets
• Message processing strategies and ensuring delivery guarantees

Kafka Integration with External Systems via Kafka Connect

• Understanding Kafka Connect and its available connectors
• Configuring and deploying Kafka Connect for data integration
• Establishing links between Kafka and external platforms

Developing Streaming Applications with Kafka Streams & ksqlDB

• Foundations of Kafka Streams and its processing capabilities
• Creating stream processing applications using Kafka Streams
• Leveraging ksqlDB for immediate data processing and analytics

Connecting Kafka Clients to Confluent Cloud

• Exploring the features of Confluent Cloud
• Configuring and connecting client applications to Confluent Cloud

Kafka Security

• Overview of Kafka’s security features
• Implementing SSL/TLS for secure communications
• Authentication and authorization frameworks within Kafka

Monitoring and Operations

• Tracking performance via metrics and monitoring tools
• Cluster and resource management strategies
• Resolving common issues and optimizing performance

Best Practices and Industry Case Studies

• Design principles for Kafka-based applications
• Real-world implementation examples across various sectors
• Constructing scalable and fault-tolerant Kafka architectures

Conclusion and Future Directions